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From |
"Joseph Coveney" <jcoveney@bigplanet.com> |

To |
<statalist@hsphsun2.harvard.edu> |

Subject |
st: Re: Predicting Random Effects from a Crossed-Level Model using xtmelogit |

Date |
Tue, 29 Dec 2009 15:13:58 +0900 |

Albert Lee wrote: This may be obvious. If so, I apologize in advance. I'm estimating a logistic model with crossed-level random effects. The outcome binary variable is fail with one fixed-effect independent binary variable refinance. The three crossed-level random effects are VAR1, VAR2 and VAR3. The STATA command I used is as below: xtmelogit fail refinance || _all:R.VAR1 || _all:R.VAR2 || _all:R.VAR3 After estimating this model, I tried to recover the random effects of VAR3 using: predict u, reffects level(VAR3) However, u only contains missing values. I would very much appreciate if someone can help me recovering these predicted random effects. -------------------------------------------------------------------------------- Doesn't -xtmelogit- use Laplace approximation by default when fitting a cross-classified model? I believe that you would need to specify at least three, or so, integration points (abscissa weights) in order to get empirical Bayes predictions of individual random effects. Joseph Coveney * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**Follow-Ups**:**st: RE: Re: Predicting Random Effects from a Crossed-Level Model using xtmelogit***From:*"Lee, Albert" <Albert.Lee@hud.gov>

**References**:**st: Predicting Random Effects from a Crossed-Level Model using xtmelogit***From:*"Lee, Albert" <Albert.Lee@hud.gov>

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